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Statistical Inference de George Casella

Statistical Inference

Autor George Casella, Roger Berger
en Limba Engleză Hardback – 18 iun 2001
This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. Intended for first-year graduate students, this book can be used for students majoring in statistics who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.
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Specificații

ISBN-13: 9780534243128
ISBN-10: 0534243126
Pagini: 688
Dimensiuni: 172 x 244 x 30 mm
Greutate: 1.04 kg
Ediția:2. Auflage
Editura: CENGAGE LEARNING INC
Locul publicării:United States

Recenzii

"Statistical Inference is a delightfully modern text on statistical theory and deserves serious consideration from every teacher of a graduate- or advanced undergraduate-level first course in statistical theory. . . Chapters 1-5 provide plenty of interesting examples illustrating either the basic concepts of probability or the basic techniques of finding distribution. . . The book has unique features [throughout Chapters 6-12] for example, I have never seen in any comparable text such extensive discussion of ancillary statistics [Ch. 6], including Basu's theorem, dealing with the independence of complete sufficient statistics and ancillary statistics. Basu's theorem is such a useful tool that it should be available to every graduate student of statistics. . . The derivation of the analysis of variance (ANOVA)F test in Chapter 11 via the union-intersection principle is very nice. . . Chapter 12 contains, in addition to the standard regression model, errors-in-variables models. This topic will be of considerable importance in the years ahead, and the authors should be thanked for giving the reader an introduction to it. . . Another nice feature is the Miscellanea Section at the end of nearly every chapter. This gives the serious student an opportunity to go beyond the basic material of the text and look at some of the more advanced work on the topics, thereby developing a much better feel for the subject."

Descriere

Casella and Berger's new edition builds the theoretical statistics from the first principals of probability theory. Thoroughly and completely, the authors start with the basics of probability and then move on to develop the theory of statistical inference using techniques, definitions, and statistical concepts.

Cuprins

1. Probability Theory.  2. Transformations and Expectations.  3. Common Families of Distributions.  4. Multiple Random Variables.  5. Properties of a Random Sample.  6. Principles of Data Reduction.  7. Point Estimation.  8. Hypothesis Testing.  9. Interval Estimation.  10. Asymptotic Evaluations.  11. Analysis of Variance and Regression.  12. Regression Models.  13. Computer Algebra.

Notă biografică

Professor George Casella completed his undergraduate education at Fordham University and graduate education at Purdue University. He served on the faculty of Rutgers University, Cornell University, and the University of Florida. His contributions focused on the area of statistics including Monte Carlo methods, model selection, and genomic analysis. He was particularly active in Bayesian and empirical Bayes methods, with works connecting with the Stein phenomenon, on assessing and accelerating the convergence of Markov chain Monte Carlo methods, as in his Rao-Blackwellisation technique, and recasting lasso as Bayesian posterior mode estimation with independent Laplace priors.
Casella was named as a Fellow of the American Statistical Association and the Institute of Mathematical Statistics in 1988, and he was made an Elected Fellow of the International Statistical Institute in 1989. In 2009, he was made a Foreign Member of the Spanish Royal Academy of Sciences.
After receiving his doctorate in statistics from Purdue University, Professor Roger Berger held academic positions at Florida State University and North Carolina State University. He also spent two years with the National Science Foundation before coming to Arizona State University in 2004. Berger is co-author of the textbook "Statistical Inference," now in its second edition. This book has been translated into Chinese and Portuguese. His articles have appeared in publications including Journal of the American Statistical Association, Statistical Science, Biometrics and Statistical Methods in Medical Research. Berger's areas of expertise include hypothesis testing, (bio)equivalence, generalized linear models, biostatistics, and statistics education.
Berger was named as a Fellow of the American Statistical Association and the Institute of Mathematical Statistics.